People prefer to predict middle, most likely quantitative outcomes (not extreme ones), but they still over-estimate their likelihood

Abstract

) with extreme quantitative outcomes, and to over-estimate the outcomes' probability of occurrence. In the first four experiments (Experiment 1, Experiments 2a-c), we tested whether this "extremity effect" reflects a general preference for extreme (vs central or less extreme) values of a distribution. Participants made predictions based on a frequency distribution in two scenarios. We did not find a preference for extreme outcomes. Instead, most of the participants made a prediction about the middle, most frequent outcome of the distribution (i.e., the modal outcome), but still over-estimated the outcomes' probabilities. In Experiment 3, we tested whether the over-estimation could be better explained by an "at least"/"at most" reading of the predictions. We found that only a minority of participants interpreted predictions as the lower/upper bounds of an open interval and that these interpretations were not associated with heightened probability estimates. In the final three experiments (Experiments 4a-c), we tested whether participants perceived extreme outcome predictions as more correct, useful and interesting than modal outcome predictions. We found that extreme and modal predictions were considered equally correct, but modal predictions were judged most useful, whereas extreme predictions were judged to be more interesting. Overall, our results indicate that the preference for extreme outcomes is limited to specific verbal probability expressions, whereas the over-estimation of the probability of quantitative outcomes may be more general than anticipated and applies to non-extreme values as well.

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